Seroprevalence and levels of IgG antibodies after COVID-19 infection or vaccination

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Abstract

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  1. SciScore for 10.1101/2021.06.06.21258406: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: The study was approved by the Research Ethics Committee of the University of Tartu.
    Consent: Informed consent was waived.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    All samples were tested for IgG antibodies against SARS-CoV-2 spike protein receptor-binding domain (anti-S-RBD IgG) by chemiluminescent microparticle immunoassay (Abbott SARS-CoV-2 IgG II Quant with ARCHITECT i2000SR analyzer; Abbott Laboratories, USA) according to the manufacturer’s instructions.
    SARS-CoV-2 spike protein receptor-binding domain (anti-S-RBD IgG
    suggested: None
    The total number of individuals with IgG antibodies was estimated by taking into account stratification to age groups and counties.
    IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    All samples were tested for IgG antibodies against SARS-CoV-2 spike protein receptor-binding domain (anti-S-RBD IgG) by chemiluminescent microparticle immunoassay (Abbott SARS-CoV-2 IgG II Quant with ARCHITECT i2000SR analyzer; Abbott Laboratories, USA) according to the manufacturer’s instructions.
    Abbott Laboratories
    suggested: None

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Several limitations in our study should be noted. First, the study design, use of leftover blood samples, may have led to somewhat biased results due to the risk of including disproportionally more sick people. Indeed, we had a somewhat larger proportion of people who had had positive PCR-test (8.2%) compared with the proportion in the whole population (4.0%). However, as the seroprevalence was similar to 21.4% (19.8-23.1%) estimated in the study on the prevalence of the coronavirus in Estonia based on a random statistical sample conducted between March 11 to March 22, 2021, [25], we believe that potential bias is small. Second, we did not have data about important covariates affecting antibody levels, particularly symptoms and sex [16, 19], and thus we were not able to adjust our analyses for these variables. Still, such impact of the study design is offset by its advantages like rapidity, low cost, no additional burden to healthcare workers or patients, avoiding physical contact that is particularly relevant in the case of COVID-19, to gain insight into the proportion of individuals protected from the disease and their antibody levels. Third, we do not know whether some individuals vaccinated had been infected with SARS-CoV-2 prior to vaccination without a positive PCR-test. As one vaccine dose after prior infection results in antibody levels similar to the titer after two doses administered to those not previously infected [26], the estimates from our model may be somewhat...

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.


    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.